摘要翻译:
我们描述了一种新的基于“反向”蒙特卡罗方法的切换算法,该算法在系统结构移动之前随机修改电势。该算法使聚类Monte Carlo方法的推广成为可能,并使离散和连续两个自由度系统的聚类算法成为可能。用该方法研究了sine-Gordon模型中的粗糙化转变,并对系统尺寸高达1024^2$的系统进行了高精度模拟,研究了表面粗糙度在转变温度以上的对数发散,揭示了Kosterlitz-Thouless型普遍标度的明显证据。
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英文标题:
《A New Monte Carlo Method and Its Implications for Generalized Cluster
Algorithms》
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作者:
C. H. Mak and Arun K. Sharma
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最新提交年份:
2007
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分类信息:
一级分类:Physics 物理学
二级分类:Soft Condensed Matter 软凝聚态物质
分类描述:Membranes, polymers, liquid crystals, glasses, colloids, granular matter
膜,聚合物,液晶,玻璃,胶体,颗粒物质
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一级分类:Physics 物理学
二级分类:Statistical Mechanics 统计力学
分类描述:Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变,热力学,场论,非平衡现象,重整化群和标度,可积模型,湍流
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英文摘要:
We describe a novel switching algorithm based on a ``reverse'' Monte Carlo method, in which the potential is stochastically modified before the system configuration is moved. This new algorithm facilitates a generalized formulation of cluster-type Monte Carlo methods, and the generalization makes it possible to derive cluster algorithms for systems with both discrete and continuous degrees of freedom. The roughening transition in the sine-Gordon model has been studied with this method, and high-accuracy simulations for system sizes up to $1024^2$ were carried out to examine the logarithmic divergence of the surface roughness above the transition temperature, revealing clear evidence for universal scaling of the Kosterlitz-Thouless type.
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PDF链接:
https://arxiv.org/pdf/704.1539